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Abstract:

In certain embodiments, a method includes storing location information
associated with a dairy livestock. The stored location information
includes a location of the dairy livestock within a free stall pen at
each of a plurality of times during a time period. The method further
includes determining, based on at least a portion of the stored location
information, one or more movement parameters associated with the dairy
livestock. The method further includes determining, based on the one or
more movement parameters associated with the dairy livestock, whether the
dairy livestock is likely unhealthy.

Claims:

1. A method for health monitoring, comprising: storing location
information associated with a dairy livestock, the location information
comprising a location of the dairy livestock within a free stall pen at
each of a plurality of times during a time period; determining, based on
at least a portion of the stored location information, one or more
movement parameters associated with the dairy livestock; and determining,
based on the one or more movement parameters associated with the dairy
livestock, whether the dairy livestock is likely unhealthy.

2. The method of claim 1, wherein the location information is generated
by a real-time location system (RTLS) comprising a plurality of
identification devices positioned throughout the free stall pen, the
plurality of identification devices each operable to, at each of a
plurality of times during the time period, generate a signal
corresponding to a tag affixed to the dairy livestock.

3. The method of claim 2, wherein communication between plurality of
identification devices and the tag affixed to the dairy livestock is
facilitated by ultra-wide band (UWB) technology.

4. The method of claim 2, wherein the RTLS is operable to determine the
location of the dairy livestock within the free stall pen at each of the
plurality of times during the time period by triangulating the signals
generated by each of the plurality of identification devices at each of a
plurality of times during a time period.

5. The method of claim 1, wherein: determining one or more movement
parameters comprises: determining a stall standing parameter
corresponding to the percentage of the time period that the dairy
livestock was standing in a stall of the free stall pen; determining a
stall lying parameter corresponding to the percentage of the time period
that the dairy livestock was lying in a stall of the free stall pen;
determining an alley walking parameter corresponding to the percentage of
the time period that the dairy livestock was walking in a walking alley
of the free stall pen; determining an alley lying parameter corresponding
to the percentage of the time period that the dairy livestock was lying
in a walking alley of the free stall pen; determining an alley standing
parameter corresponding to the percentage of the time period that the
dairy livestock was standing stationary in a walking alley of the free
stall pen; determining a feeding parameter corresponding to the
percentage of the time period that the dairy livestock was located within
a predefined distance of a feed lane of the free stall pen; determining a
watering parameter corresponding to the percentage of the time period
that the dairy livestock was located within a predefined distance of a
water trough of the free stall pen; and determining a health index
corresponding to a function of the stall standing parameter, the stall
lying parameter, the alley walking parameter, the alley lying parameter,
the alley standing parameter, the feeding parameter, and the watering
parameter; and determining, based on one or more movement parameters
associated with the dairy livestock, whether the dairy livestock is
likely unhealthy comprises determining whether the determined health
index is in excess of a baseline health index by more than a predefined
amount.

6. The method of claim 5, wherein the baseline health index comprises an
average health index for a plurality of other dairy livestock in the free
stall during a previous time period.

7. The method of claim 5, wherein the baseline health index comprises a
health index for the dairy livestock during a previous time period.

8. A system for health monitoring, comprising: one or more memory modules
operable to store location information associated with a dairy livestock,
the location information comprising a location of the dairy livestock
within a free stall pen at each of a plurality of times during a time
period; and one or more processing modules operable to: determine, based
on at least a portion of the stored location information, one or more
movement parameters associated with the dairy livestock; and determine,
based on the one or more movement parameters associated with the dairy
livestock, whether the dairy livestock is likely unhealthy.

9. The system of claim 8, wherein the location information is generated
by a real-time location system (RTLS) comprising a plurality of
identification devices positioned throughout the free stall pen, the
plurality of identification devices each operable to, at each of a
plurality of times during the time period, generate a signal
corresponding to a tag affixed to the dairy livestock.

10. The system of claim 9, wherein communication between plurality of
identification devices and the tag affixed to the dairy livestock is
facilitated by ultra-wide band (UWB) technology.

11. The system of claim 9, wherein the RTLS is operable to determine the
location of the dairy livestock within the free stall pen at each of the
plurality of times during the time period by triangulating the signals
generated by each of the plurality of identification devices at each of a
plurality of times during a time period.

12. The system of claim 8, wherein: determining one or more movement
parameters comprises: determining a stall standing parameter
corresponding to the percentage of the time period that the dairy
livestock was standing in a stall of the free stall pen; determining a
stall lying parameter corresponding to the percentage of the time period
that the dairy livestock was lying in a stall of the free stall pen;
determining an alley walking parameter corresponding to the percentage of
the time period that the dairy livestock was walking in a walking alley
of the free stall pen; determining an alley lying parameter corresponding
to the percentage of the time period that the dairy livestock was lying
in a walking alley of the free stall pen; determining an alley standing
parameter corresponding to the percentage of the time period that the
dairy livestock was standing stationary in a walking alley of the free
stall pen; determining a feeding parameter corresponding to the
percentage of the time period that the dairy livestock was located within
a predefined distance of a feed lane of the free stall pen; determining a
watering parameter corresponding to the percentage of the time period
that the dairy livestock was located within a predefined distance of a
water trough of the free stall pen; and determining a health index
corresponding to a function of the stall standing parameter, the stall
lying parameter, the alley walking parameter, the alley lying parameter,
the alley standing parameter, the feeding parameter, and the watering
parameter; and determining, based on one or more movement parameters
associated with the dairy livestock, whether the dairy livestock is
likely unhealthy comprises determining whether the determined health
index is in excess of a baseline health index by more than a predefined
amount.

13. The system of claim 12, wherein the baseline health index comprises
an average health index for a plurality of other dairy livestock in the
free stall during a previous time period.

14. The system of claim 12, wherein the baseline health index comprises a
health index for the dairy livestock during a previous time period.

15. A method for health monitoring, comprising: storing location
information associated with a dairy livestock, the location information
comprising a coordinate location of the dairy livestock within a free
stall pen at each of a plurality of times during a time period, the
location information having been generated by a real-time location system
(RTLS) comprising a plurality of identification devices positioned
throughout the free stall pen, the plurality of identification devices
each operable to, at each of the plurality of times during the time
period, generate a signal corresponding to a tag affixed to the dairy
livestock; determining a stall standing parameter corresponding to the
percentage of the time period that the dairy livestock was standing in a
stall of the free stall pen; determining a stall lying parameter
corresponding to the percentage of the time period that the dairy
livestock was lying in a stall of the free stall pen; determining an
alley walking parameter corresponding to the percentage of the time
period that the dairy livestock was walking in a walking alley of the
free stall pen; determining an alley lying parameter corresponding to the
percentage of the time period that the dairy livestock was lying in a
walking alley of the free stall pen; determining an alley standing
parameter corresponding to the percentage of the time period that the
dairy livestock was standing stationary in a walking alley of the free
stall pen; determining a feeding parameter corresponding to the
percentage of the time period that the dairy livestock was located within
a predefined distance of a feed lane of the free stall pen; determining a
watering parameter corresponding to the percentage of the time period
that the dairy livestock was located within a predefined distance of a
water trough of the free stall pen; and determining whether a heath index
for the dairy livestock is in excess of a baseline health index by more
than a predefined amount, the health index for the dairy livestock
corresponding to a function of the stall standing parameter, the stall
lying parameter, the alley walking parameter, the alley lying parameter,
the alley standing parameter, the feeding parameter, and the watering
parameter.

Description:

TECHNICAL FIELD

[0001] This invention relates generally to dairy farming and more
particularly to a system and method for health monitoring using real-time
location.

BACKGROUND OF THE INVENTION

[0002] For modern dairy milking operations to remain profitable, it may be
important to maximize the efficiency of a herd of dairy livestock. In
order to maximize efficiency of a herd of dairy livestock, it may be
important to ensure that the herd of dairy livestock remains healthy and
has a high reproductive efficiency. Accordingly, health monitoring and
estrus detection for a herd of dairy livestock may be integral components
of modern dairy milking operations. Current systems and methods
supporting health monitoring and estrus detection, however, have proven
inadequate in various respects.

SUMMARY OF THE INVENTION

[0003] According to embodiments of the present disclosure, disadvantages
and problems associated with previous systems and methods for health
monitoring may be reduced or eliminated.

[0004] In certain embodiments, a method includes storing location
information associated with a dairy livestock. The stored location
information includes a location of the dairy livestock within a free
stall pen at each of a plurality of times during a time period. The
method further includes determining, based on at least a portion of the
stored location information, one or more movement parameters associated
with the dairy livestock. The method further includes determining, based
on the one or more movement parameters associated with the dairy
livestock, whether the dairy livestock is likely unhealthy.

[0005] Particular embodiments of the present disclosure may provide one or
more technical advantages. For example, certain embodiments of the
present disclosure may facilitate an automated determination regarding
whether each of the dairy livestock in a herd is likely unhealthy based
on the movement of the dairy livestock within a free stall pen. Because a
healthy herd of dairy livestock may have a greater quantity and/or
quality of milk production, certain embodiments of the present disclosure
may facilitate an increase in the overall milk output and/or quality for
a herd of dairy livestock.

[0006] Certain embodiments of the present disclosure may include some,
all, or none of the above advantages. One or more other technical
advantages may be readily apparent to those skilled in the art from the
figures, descriptions, and claims included herein.

BRIEF DESCRIPTION OF THE DRAWINGS

[0007] To provide a more complete understanding of the present invention
and the features and advantages thereof, reference is made to the
following description taken in conjunction with the accompanying
drawings, in which:

[0008] FIG. 1 illustrates a logical view of an example system for estrus
detection and health monitoring using real-time location, according to
certain embodiments of the present disclosure; and

[0009]FIG. 2 illustrates an example method for estrus detection using
real-time location, according to certain embodiments of the present
disclosure; and

[0010] FIG. 3 illustrates an example method for health monitoring using
real-time location, according to certain embodiments of the present
disclosure.

DETAILED DESCRIPTION OF THE DRAWINGS

[0011] FIG. 1 illustrates a logical view of an example system 100 for
estrus detection and health monitoring using real-time location,
according to certain embodiments of the present disclosure. System 100
includes a free stall pen 102 housing a number of dairy livestock 104.
Free stall pen 102 may be configured to include a number of stalls 106,
walking lanes 108, and water troughs 110, and may be positioned adjacent
to a feed lane 112. System 100 further includes a number of
identification devices 114 positioned throughout free stall pen 102, each
identification device 114 being configured to (1) read tags affixed to
each of the dairy livestock 104, and (2) communicate with a controller
116. Although this particular implementation of system 100 is illustrated
and primarily described, the present disclosure contemplates any suitable
implementation of system 100 according to particular needs. Additionally,
although the present disclosure contemplates free stall pen 102 housing
any suitable dairy livestock 104 (e.g., cows, goats, sheep, water
buffalo, etc.), the remainder of this description is detailed with
respect to dairy cows.

[0012] Free stall pen 102 may include any suitable number of walls
dividing free stall pen 102 into a number of stalls 106 and a number
walking lanes 108. The walls of free stall pen 102 may be constructed of
any suitable materials arranged in any suitable configuration operable to
manage the movement of dairy cows 104. For example, the walls of free
stall pen 102 may each include any number and combination of posts,
rails, tubing, rods, connectors, cables, wires, and/or beams operable to
form a substantially planar barricade such as a fence, wall, and/or other
appropriate structure suitable to manage the movement of dairy cows 104.
Free stall pen 102 may additionally include a number of water troughs 110
each positioned at any suitable location within free stall pen 102 such
that dairy cows 104 may access drinking water.

[0013] Free stall pen 102 may be positioned adjacent to a feed lane 112.
Feed lane 112 may be configured to permit a vehicle to pass through feed
lane 112 and distribute feed for dairy cows 104 located in free stall pen
102. For example, feed lane 112 may be separated from free stall pen 102
by a wall comprising a number of slots sized such that dairy cows 104 may
extend their heads into feed lane 112 and eat feed distributed in feed
lane 112.

[0014] A number of identification devices 114 may be positioned at various
locations within and/or adjacent to free stall pen 102. Although a
particular number of identification devices 114 are illustrated as being
positioned at particular locations within free stall pen 102, the present
disclosure contemplates any suitable number of identification devices 114
located at any suitable positions within and/or adjacent to free stall
pen 102, according to particular needs.

[0015] Identification devices 114 may each include any suitable device
operable to receive a signal from a tag affixed to a dairy cow 104 (e.g.,
an ear tag) located in free stall pen 102. In response to a signal
received from a tag affixed to a dairy cow 104, identification devices
114 may generate a signal corresponding to that tag for communication to
controller 116 (described below). Communication between identification
devices 114 and tags affixed to dairy cows 104 may be facilitated by any
suitable technology, including, for example, passive radio-frequency
identification (RFID), active RFID, Wi-Fi, Bluetooth, ultra-wide band
(UWB), ZigBee, acoustic locating, and computer vision. In certain
embodiments, a generated signal corresponding to a tag affixed to a dairy
cow 104 may include (1) an identification number related to the dairy cow
104, (2) the distance, angle, and/or other information concerning the
location of the dairy cow 104 relative to the identification device 114
generating the signal, (3) an identification of the identification device
114 generating the signal, and/or (4) a timestamp.

[0016] Identification devices 114 may be communicatively coupled (e.g.,
via a network facilitating wireless or wireline communication) to
controller 116. Controller 116 may include one or more computer systems
at one or more locations. Each computer system may include any
appropriate input devices (such as a keypad, touch screen, mouse, or
other device that can accept information), output devices, mass storage
media, or other suitable components for receiving, processing, storing,
and communicating data. Both the input devices and output devices may
include fixed or removable storage media such as a magnetic computer
disk, CD-ROM, or other suitable media to both receive input from and
provide output to a user. Each computer system may include a personal
computer, workstation, network computer, kiosk, wireless data port,
personal data assistant (PDA), one or more processors within these or
other devices, or any other suitable processing device. In short,
controller 116 may include any suitable combination of software,
firmware, and hardware.

[0017] Controller 116 may additionally include one or more processing
modules 118 and one or more memory modules 120 (each referred to in the
singular throughout the remainder of this description). Processing module
118 may include one or more microprocessors, controllers, or any other
suitable computing devices or resources and may work, either alone or
with other components of system 100, to provide a portion or all of the
functionality of system 100 described herein. Memory module 120 may take
the form of volatile or non-volatile memory including, without
limitation, magnetic media, optical media, random access memory (RAM),
read-only memory (ROM), removable media, or any other suitable memory
component.

[0018] Controller 116 may additionally include real-time location (RTL)
logic 122, estrus detection logic 124, and health monitoring logic 126
(e.g., each stored memory module 120). RTL logic 122 (which, in
combination with identification devices 114 and the plurality of tags
affixed to the plurality of dairy cows 104, may be referred to as a
real-time location system (RTLS)) may include any information, logic,
and/or instructions stored and/or executed by controller 116 to determine
location information 128 associated with dairy cows 104 in free stall pen
102 based on signals received from identification devices 114 (as
described in further detail below). Estrus detection logic 124 may
include any information, logic, and/or instructions stored and/or
executed by controller 116 to determine, based on the location
information 128 associated with a particular dairy cow 104 generated by
RTL logic 122, whether the particular dairy cow 104 is likely to be in
estrus (as described in further detail below). Health monitoring logic
126 may include any information, logic, and/or instructions stored and/or
executed by controller 116 to determine, based on the location
information 128 associated with a particular dairy cow 104 generated by
RTL logic 122, whether the particular dairy cow 104 is likely unhealthy
(as described in further detail below). Although certain functionality is
described below as being associated with RTL logic 122, estrus detection
logic 124, or health monitoring logic 126, the present disclosure
contemplates the functionality described below as being combined or
divided among any suitable logic, according to particular needs.

[0019] Controller 116 may be operable to receive signals generated by
identification devices 114. In certain embodiments, controller 116 may
receive signals corresponding to each dairy cow 104 in free stall pen 102
from each identification device 114. Furthermore, for a particular dairy
cow 104, controller 116 may receive signals from each identification
device 114 at or about the same time and at regular intervals (e.g.,
every fifteen seconds). For example, for a particular dairy cow 104 at a
particular time, controller 116 may receive signals generated by a number
of identification devices 114 (e.g., each signal identifying the
particular dairy cow 104 and the distance the particular dairy cow 104 is
located from the corresponding identification device 114). Based on the
received signals, controller 116 may determine location information 128
associated with the particular dairy cow 104 at the particular time
(e.g., using RTL logic 122, as described below).

[0020] In certain embodiments, RTL logic 122 may be operable to process
signals received from identification devices 114 in order to determine
location information 128 associated with dairy cows 104 in free stall pen
102. As described above, a particular subset of the received signals may
be generated by the identification devices 114 at approximately the same
time and may identify the same particular dairy cow 104. Each of the
signals of the particular subset may additionally include information
about the position of the particular dairy cow 104 relative to the
corresponding identification device 114 (e.g., distance, angle, etc.).
Based on one or more of the subset of received signals, RTL logic 122 may
determine a coordinate location of the particular dairy cow 104 within
free stall pen 102. In certain embodiments, the determined coordinate
location may be an (X,Y) location within the free stall pen 102. In
certain other embodiments, the determined coordinate location may be an
(X,Y,Z) location within the free stall pen 102.

[0021] As just one example, RTL logic 122 may determine a coordinate
location of the particular dairy cow 104 within free stall pen 102 using
triangulation (based on at least three of the subset of received
signals). Because each of the at least three signals may include
information about the position of the particular dairy cow 104 (e.g.,
distance and/or angle) relative to the corresponding identification
device 114 and the location of each corresponding identification device
114 within free stall pen 102 may be known, the coordinate location
(e.g., an (X,Y) location, an (X,Y,Z) location, or any other suitable
coordinate location) of the particular dairy cow 104 within free stall
pen 102 may be determined.

[0022] Furthermore, because controller 116 may receive signals from
identification devices 114 for each dairy cow 104 on a periodic basis
(e.g., every fifteen seconds), location information 128 may be generated
for each dairy cow 104 in free stall pen 102 at each of a number of times
during a particular time period (e.g., every fifteen seconds over a one
hour period). The generated location information 128 associated with each
dairy cow 104 may then be stored (e.g., in memory module 120 or any other
suitable location in system 100) such that the location information 128
may be later accessed (e.g., by estrus detection logic 124 and health
monitoring logic 126, as described in further detail below).

[0023] In certain embodiments, estrus detection logic 124 may be operable
to access location information 128 associated with each dairy cow 104 in
free stall pen 102 and determine, based on at least a portion of that
location information 128, one or more movement parameters 130 associated
with each dairy cow 104. The determined movement parameters 130 for dairy
cows 104 may be stored (e.g., in memory module 120) such that changes in
the movement parameters 130 may be assessed over time. Because the
movement of a dairy cow 104 within free stall pen 102 (as reflected by
the movement parameters 130, which are described in detail below) may be
indicative of whether the dairy cow 104 is in estrus, the movement
parameters 130 may be used by estrus detection logic 124 to determine
whether the dairy cow 104 is likely to be in estrus (as described below).

[0024] In certain embodiments, the movement parameters 130 for a
particular dairy cow 104 may include a percentage of a particular time
period (e.g., one hour) the particular dairy cow 104 spent in each of a
number of areas of free stall pen 102. For example, the movement
parameters 130 may include (1) a percentage of time the particular dairy
cow 104 spent standing in a stall 106 of free stall pen 102 (stall
standing parameter 134), (2) a percentage of time the particular dairy
cow 104 spent lying in a stall 106 of free stall pen 102 (stall lying
parameter 136), (3) a percentage of time the particular dairy cow 104
spent walking in a walking alley 108 of free stall pen 102 (alley walking
parameter 138), (4) a percentage of time the particular dairy cow 104
spent lying in a walking alley 108 of free stall pen 102 (alley lying
parameter 140), (5) a percentage of time the particular dairy cow 104
spent standing in a walking alley 108 of free stall pen 102 (alley
standing parameter 142) (6) a percentage of time the particular dairy cow
104 spent near a water trough 110 (watering parameter 144), and/or (7) a
percentage of time the particular dairy cow 104 spent near feed lane 112
(feeding parameter 146).

[0025] The above-described movement parameters 130 for a particular dairy
cow 104 may be determined by comparing the location information 128 for
the particular dairy cow 104 collected during a particular time period
(including a number of coordinate locations for the particular dairy cow
104 at a number of discrete times during the particular time period, as
described above) with layout information 132 for free stall pen 102
(e.g., stored in memory module 120). In certain embodiments, layout
information 132 for free stall pen 102 may include coordinate locations
defining the corners of each stall 106 (and thus defining the area within
each stall 106), coordinate locations defining the corners of each
walking lane 108 (and thus defining the area within each walking lane
108), coordinate locations defining the corners of the area around each
water trough 110 (and thus defining a watering area), and the corners of
the area near feed lane 112 (and thus defining a feeding area). For each
coordinate location for the particular dairy cow 104 within these defined
areas, the area in which the particular dairy cow 104 is located at each
discrete time during the time period may be determined.

[0026] For example, location information 128 for a particular dairy cow
104 may include coordinate locations of the particular dairy cow 104 at
discrete times (e.g., every fifteen seconds) during a particular time
period (e.g., one hour). By comparing each (X,Y) coordinate location of
the particular dairy cow 104 with layout information 132 for free stall
pen 102, the position of the particular dairy cow 104 within free stall
pen 102 may be determined at each discrete time during the time period.
Moreover, if it is assumed that the position of the particular dairy cow
104 remains constant from one discrete time to the next (e.g., for the
fifteen second time period until a new coordinate location for the
particular dairy cow 104 is available), a percentage of the particular
time period that the particular dairy cow 104 spent in various locations
within the free stall pen 102 may be determined. Furthermore, in
embodiments in which the coordinate location for the particular dairy cow
104 includes a (Z) location, a percentage of the particular time period
that the particular dairy cow 104 spent standing versus lying at each
location may additionally be determined (as a (Z) location for the
particular dairy cow 104 in both a standing and lying position may be
known). From this information, the above-described movement parameters
130 (e.g., a stall standing parameter 134, a stall lying parameter 136,
an alley walking parameter 138, an alley lying parameter 140, an alley
standing parameter 142, a watering parameter 144, and a feeding parameter
146) may be determined.

[0027] In certain embodiments, the movement parameters 130 for a
particular dairy cow 104 may additionally include a watering count 148
and a feeding count 150. The watering count 148 may correspond to the
number of times during a time period that the particular dairy cow 104
moves within a predetermined distance (e.g., five feet) of a water trough
110. Similarly, the feeding count 150 may correspond to the number of
times during a time period that the particular dairy cow 104 moves within
a predetermined distance (e.g., five feet) of feed lane 112.
Additionally, in embodiments in which location information 128 includes a
(Z) coordinate location, movement parameters 130 for a particular dairy
cow 104 may additionally include a mounting count 152. The mounting count
152 may correspond to the number of times during a particular time period
that the (Z) coordinate location of the particular dairy cow 104
increasing above a particular threshold (indicating that the particular
dairy cow 104 has mounted another dairy cow 104).

[0028] In certain embodiments, the movement parameters 130 for a
particular dairy cow 104 may additionally include a mobility count 154.
The mobility count 154 may correspond to the number of times during a
time period that the particular dairy cow 104 moves more than a
predetermined distance (e.g., five feet) between consecutive discrete
times for which a coordinate location is available for the particular
dairy cow 104 (e.g., during the fifteen second interval between times
that identification devices 114 generate signals corresponding to the
particular dairy cow 104). As just one example, in embodiments in which
the location information 128 for the particular dairy cow 104 includes
(X,Y) location for the particular dairy cow 104 at a number of discrete
times (t), the mobility count 154 may be determined as follows:

[0029] If

[X(t+1)-X(t)]>5 feet

or

[Y(t+1)-Y(t)]>5 feet

[0030] then increase mobility count by 1

In certain embodiments, the mobility count 154 may be normalized to
determine a mobility count per hour by dividing the determined mobility
count 154 by the number of hours in the time period during which the
mobility count 154 was determined.

[0031] In certain embodiments, the movement parameters 130 for a
particular dairy cow 104 may additionally include a distance traveled 156
by the particular dairy cow 104 during a time period. As just one
example, in embodiments in which the location information 128 for the
particular dairy cow 104 includes (X,Y) location for the particular dairy
cow 104 at a number of discrete times (t), the distance traveled 156 by
the particular dairy cow 104 may be determined as follows:

In certain embodiments, the distance traveled 156 by the particular dairy
cow 104 in a time period may be normalized to determine a distance
traveled per hour by dividing the determined distance traveled 156 by the
number of hours in the time period for which the distance traveled 156
was determined.

[0032] In certain embodiments, the movement parameters 130 for a
particular dairy cow 104 may additionally include a turn count 158. The
turn count 158 may correspond to the number of times during a time period
that the particular dairy cow 104 changes direction between consecutive
discrete times for which a coordinate location is available for the
particular dairy cow 104 (e.g., the difference in angular direction of
the particular dairy cow 104 from discrete time to the next changes less
than 90° or more than 270°). As just one example, in
embodiments in which the location information for the particular dairy
cow 104 includes (X,Y) location for the particular dairy cow 104 at a
number of discrete times (t), the turn count 158 for the particular dairy
cow 104 may be determined as follows:

In certain embodiments, the turn count 158 may be normalized to determine
a number of turns per hour by dividing the determined turn count 158 by
the number of hours in the time period for which the turn count 158 was
determined.

[0036] In certain embodiments, the movement parameters 130 for a
particular dairy cow 104 may additionally include a sign change count
160. Like the turn count 158, the sign change count 160 may correspond to
the number of times during a time period that the particular dairy cow
104 changes direction between consecutive discrete times for which a
coordinate location is available for the particular dairy cow 104. As
just one example, in embodiments in which the location information for
the particular dairy cow 104 includes (X,Y) location for the particular
dairy cow 104 at a number of discrete times (t), the sign change count
160 for the particular dairy cow 104 may be determined as follows:

[0037] If

[X(t+1)-X(t)]>0 and [X(t+2)-X(t+1)]<0 (or vice versa)

or

[Y(t+1)-Y(t)]>0 and [Y(t+2)-Y(t+1)]<0 (or vice versa)

[0038] then increase sign change count by 1

In certain embodiments, the sign change count 160 may be normalized to
determine a number of sign changes per hour by dividing the determined
sign change count 160 by the number of hours in the time period for which
the sign change count 160 was determined.

[0039] Estrus detection logic 124 may additionally be operable to
determine, based on one or more of the above-described movement
parameters 130 associated with dairy cows 104 (determined based on
coordinate locations for the particular dairy cow 104 during a particular
time period, as described above), which of the dairy cows 104 are likely
to be in estrus at a given time.

[0040] For example, estrus detection logic 124 may determine if a
particular dairy cow 104 is likely to be in estrus by comparing a "heat
index" for the particular dairy cow 104 (described below) with a baseline
heat index. In certain embodiments, the heat index for a particular dairy
cow 104 may correspond to the product of an alley walking parameter 138
and a normalized mobility count 154 (e.g., heat index=(alley walking
parameter)×(mobility count/hour)). In such embodiments, the heat
index may be indicative of the amount of movement of the particular dairy
cow 104, with a certain amount of increase in movement of the particular
dairy cow 104 (e.g., 250% over a baseline, as described below) being an
indicator that the particular dairy cow 104 is in estrus.

In such embodiments, the heat index may be indicative of an increase in
certain activity of the particular dairy cow 104 (e.g., walking in
walking lanes 108, pacing, and/or mounting other dairy cows 104), with an
increase in such activity being an indicator that the particular dairy
cow 104 is in estrus. Although particular constants a-n are listed as
being used to calculate the heat index for example purposes, the present
disclosure contemplates any suitable constants, according to particular
needs.

[0057] If the heat index for particular dairy cow 104 is greater than the
baseline heat index by more than a predefined amount (e.g., 250%), estrus
detection logic 124 may determine that the particular dairy cow 104 is
likely to be in estrus (as such an increase may indicate either that (1)
the amount of movement of the particular dairy cow 104 has increased or
(2) the particular dairy cow 104 is spending time in those portions of
the free stall pen 102 in which a dairy cow 104 likely to be in estrus is
likely to be located, such as walking lanes 108). The baseline heat index
may be (1) a heat index for the particular dairy cow 104 during a
previous time period (e.g., the previous twenty-four hours), (2) an
average heat index for one or more other dairy cows 104 in free stall pen
102 during a previous time period (e.g., the previous twenty-four hours),
(3) a user defined baseline heat index, or (4) any other suitable
baseline heat index, according to particular needs. In certain
embodiments, the baseline heat index may take into account the ambient
conditions in the free stall pen 102 (e.g., temperature), as the movement
of dairy cows 104 within free stall pen 102 may vary based on those
conditions.

[0058] As another example, estrus detection logic 124 may compare a
distance traveled 156 by the particular dairy cow 104 (e.g., a distance
traveled per hour during a particular time period, as described above)
with a baseline distance traveled. If the distance traveled 156 by the
particular dairy cow 104 is greater than the baseline distance traveled
by more than a predefined amount (e.g., 250%), estrus detection logic 124
may determine that the particular dairy cow 104 is likely to be in estrus
(as an increase in movement of the particular dairy cow 104 may be an
indicator that the particular dairy cow 104 is in estrus). The baseline
distance traveled may be (1) a distance traveled by the particular dairy
cow 104 during a previous time period (e.g., the distance traveled per
hour during the previous twenty-four hours), (2) an average distance
traveled by one or more other dairy cows 104 in free stall pen 102 during
a previous time period (e.g., the average distance traveled per hour
during the previous twenty-four hours), (3) a user defined baseline
distance traveled, or (4) any other suitable baseline distance traveled,
according to particular needs. In certain embodiments, the baseline
distance traveled may take into account the ambient conditions in the
free stall pen 102 (e.g., temperature), as the movement of dairy cows 104
within free stall pen 102 may vary based on those conditions.

[0059] As yet another example, estrus detection logic 124 may compare a
"turn index" for a particular dairy cow 104 (described below) with a
baseline turn index. In certain embodiments, the turn index may
correspond to the sum of turn count 158 and sign change count 160 (e.g.,
turn index=(turn count)+(sign change count)). In such embodiments, the
turn index may be indicative of pacing by the particular dairy cow 104,
which may be an indicator that the particular dairy cow 104 is in estrus.

[0060] If the turn index for particular dairy cow 104 is greater than the
baseline turn index by more than a predefined amount (e.g., 250%), estrus
detection logic 124 may determine that the particular dairy cow 104 is
likely to be in estrus (as such an increase may be indicative of an
increase in pacing by the particular dairy cow 104, which may be
indicative of estrus). The baseline turn index may be (1) a turn index
for the particular dairy cow 104 during a previous time period (e.g., the
previous twenty-four hours), (2) an average turn index for one or more
other dairy cows 104 in free stall pen 102 during a previous time period
(e.g., the previous twenty-four hours), (3) a user defined baseline turn
index, or (4) any other suitable baseline turn index, according to
particular needs. In certain embodiments, the baseline turn index may
take into account the ambient conditions in the free stall pen 102 (e.g.,
temperature), as the movement of dairy cows 104 within free stall pen 102
may vary based on those conditions.

[0061] Having determined that a particular dairy cow 104 is likely to be
in estrus, estrus detection logic 124 may be further operable to confirm
that determination. For example, in response to a determination that a
particular dairy cow 104 is likely to be in estrus, estrus detection
logic 124 may access stored information associated with the particular
dairy cow 104 (e.g., stored in memory module 120) to determine if the
particular dairy cow 104 is near the twenty-first day of her cycle. A
determination that the particular dairy cow 104 is near the twenty-first
day of her cycle may provide further confirmation that the particular
dairy cow 104 is likely to be in estrus.

[0062] As an additional example, in response to a determination that a
particular dairy cow 104 is likely to be in estrus, estrus detection
logic 124 may initiate the generation of a signal to be communicated to
identification devices 114, the signal causing identification devices 114
to increase the frequency with which the tag of the particular dairy cow
104 is read (e.g., from fifteen seconds to five seconds). As a result,
updated location information 128 may be generated by RTL logic 122
(including coordinate locations for the particular dairy cow 104 at more
closely spaced intervals). Based on that updated location information
128, one or more of the above-described movement parameters 130 may be
recalculated, and estrus detection logic 124 may make a subsequent
determination regarding whether the particular dairy cow 104 is likely to
be in estrus (in a manner substantially similar to that described above)
in order to further confirm the original estrus determination. In certain
embodiments, the frequency with which the tag of the particular dairy cow
104 is read may revert to the default frequency (e.g., fifteen seconds)
in response to the expiration of a predetermined period of time (e.g.,
one hour), in response to user input, or in response to any other
suitable trigger.

[0063] As yet another example, in response to a determination that a
particular dairy cow 104 is likely to be in estrus, estrus detection
logic 124 may access location information 128 for other dairy cows 104 in
free stall pen 102 to identify those other dairy cows 104 within a
predefined distance of the particular dairy cow 104. Estrus detection
logic 124 may monitor location information 128 of the identified other
dairy cows 104 to determine if there are any increases in the (Z)
coordinate location for the identified other dairy cows 104. An increase
in the (Z) coordinate location of another dairy cow 104 located near the
particular dairy cow 104 may indicate that the other dairy cow 104 is
mounting the particular dairy cow 104, which may provide further
confirmation that the particular dairy cow 104 is in estrus.

[0064] As yet another example, in response to a determination that a
particular dairy cow 104 is in estrus, estrus detection logic 124 may
access location information 128 for other dairy cows 104 in free stall
pen 102 to identify those other dairy cows 104 within a predefined
distance of the particular dairy cow 104. Estrus detection logic 124 may
then monitor the location of the identified other dairy cows 104 to
determine if any remain within a predefined distance of the particular
dairy cow 104 for an extended period of time (e.g., one hour). Certain of
the identified other dairy cows 104 remaining near the particular dairy
cow 104 may indicate the presence of a sexually active group (SAG) (i.e.,
a group of dairy cows 104 which are each in estrus). Determining that the
particular dairy cow 104 is a member of a SAG may provide further
confirmation that the particular dairy cow 104 is likely to be in estrus.

[0065] Having determined that one or more dairy cows 104 are likely to be
in estrus (and possibly subsequent to confirming those determinations),
estrus detection logic 124 may create exception reports to be stored in
association with the one or more dairy cows 104 (e.g., in memory module
120). Additionally or alternatively, estrus detection logic 124 may
initiate the communication of reports (e.g., emails) to the farmer for
each of the one or more dairy cows 104 such that the farmer may further
monitor the one or more dairy cows 104 and/or remove the one or more
dairy cows 104 from the free stall pen 102 for breeding. In certain
embodiments, a report communicated to a farmer may indicate the relative
strength of the estrus determination.

[0066] In certain embodiments, health monitoring logic 126 may be operable
to access location information 128 associated with each dairy cow 104 in
free stall pen 102 and determine, based on at least a portion of that
location information, one or more movement parameters 130 associated with
each dairy cow 104. For example, health monitoring logic 126 may
determine movement parameters 130 including a percentage of a particular
time period (e.g., one hour) the dairy cows 104 spent in each of a number
of areas of free stall pen 102. For example, health monitoring logic 126
may determine a stall standing parameter 134, a stall lying parameter
136, an alley walking parameter 138, an alley lying parameter 140, an
alley standing parameter 142, a watering parameter 144, a feeding
parameter 146, a watering count 148, and/or a feeding count 150 in a
manner substantially similar to that described above. The determined
movement parameters 130 for dairy cows 104 may be stored (e.g., in memory
module 120) such that changes in the movement parameters 130 may be
assessed over time. Because the movement of a dairy cow 104 within free
stall pen 102 may be indicative of whether the dairy cow 104 is likely
unhealthy, the movement parameters may be used by health monitoring logic
126 to determine if one or more dairy cows 104 are unhealthy (as
described below).

[0067] Although health monitoring logic 126 and estrus detection logic 124
are each described as determining common movement parameters for dairy
cows 104, the present disclosure contemplates those parameters being
calculated by health monitoring logic 126, estrus detection logic 124, or
by any other suitable logic (e.g., RTL logic 122) such that the movement
parameters may be shared between health monitoring logic 126 and estrus
detection logic 124.

[0068] Health monitoring logic 126 may additionally be operable to
determine, based on one or more of the above-described movement
parameters 130 associated with dairy cows 104 (determined based
coordinate locations for the particular dairy cow 104 during a particular
time period, as described above), which of the dairy cows 104 are
unhealthy at a given time. For example, health monitoring logic 126 may
compare a "health index" for a particular dairy cow 104 (described below)
with a baseline health index. In certain embodiments, the health index
for the particular dairy cow 104 may correspond to a function of a stall
standing parameter 134, a stall lying parameter 136, an alley walking
parameter 138, an alley lying parameter 140, an alley standing parameter
142 a watering parameter 144, a feeding parameter 146, a watering count
148, and/or a feeding count 150. As just one example, the health index
may be calculated as follows:

In such embodiments, the health index may be indicative of an amount of
time the particular dairy cow 104 spent in each of the various portions
of free stall pen 102, with an increase in activity in certain portions
of free stall pen 102 (e.g., an increase in the amount of time spent
lying in walking alleys 108) being an indicator that the particular dairy
cow 104 is unhealthy. Although particular constants a-n are listed as
being used to calculate the health index for example purposes, the
present disclosure contemplates any suitable constants, according to
particular needs.

[0084] If the health index for particular dairy cow 104 is greater than
the baseline health index by more than a predefined amount (e.g., 250%),
health monitoring logic 126 may determine that the particular dairy cow
104 is likely unhealthy. The baseline health index may be (1) a health
index for the particular dairy cow 104 during a previous time period
(e.g., the previous twenty-four hours), (2) an average health index for
one or more other dairy cows 104 in free stall pen 102 during a previous
time period (e.g., the previous twenty-four hours), (3) a user defined
baseline health index, or (4) any other suitable baseline health index,
according to particular needs.

[0085] Having determined that a particular dairy cow 104 is likely
unhealthy, health monitoring logic 126 may be operable to confirm that
determination. For example, health monitoring logic 126 may initiate the
generation of a signal to be communicated to identification devices 114,
the signal causing identification devices 114 to increase the frequency
with which the tag of the particular dairy cow 104 is read (e.g., from
fifteen seconds to five seconds). As a result, updated location
information 128 may be generated by RTL logic 122 (including coordinate
locations for the particular dairy cow 104 at more closely spaced
intervals). Based on that updated location information 128, one or more
of the above-described movement parameters 130 may be recalculated, and
health monitoring logic 126 may make a subsequent determination regarding
whether the particular dairy cow 104 is likely unhealthy (in a manner
substantially similar to that described above) in order to further
confirm the original unhealthy determination. In certain embodiments, the
frequency with which the tag of the particular dairy cow 104 is read may
revert to the default frequency (e.g., fifteen seconds) in response to
the expiration of a predetermined period of time (e.g., one hour), in
response to user input, or in response to any other suitable trigger.

[0086] Having determined that one or more dairy cows 104 are unhealthy
(and possibly subsequent to confirming those determinations), health
monitoring logic 126 may create exception reports to be stored in
association with the one or more dairy cows 104 (e.g., in memory module
120). Additionally or alternatively, health monitoring logic 126 may
initiate the communication of reports (e.g., emails) to the farmer for
each of the one or more dairy cows 104 such that the farmer may further
monitor the one or more dairy cows 104 and/or remove the one or more
dairy cows 104 from the free stall pen 102 for medical attention. In
certain embodiments, a report communicated to a farmer may indicate the
relative strength of the determination that a dairy cow 104 is likely
unhealthy.

[0087] Although a particular implementation of system 100 is illustrated
and primarily described, the present disclosure contemplates any suitable
implementation of system 100, according to particular needs.

[0088]FIG. 2 illustrates an example method 200 for estrus detection,
according to certain embodiments of the present disclosure. Although
method 200 is described with regard to a particular dairy cow 104, the
present disclosure contemplates a substantially similar method being
performed with regard to each of the plurality of dairy cows 104 in free
stall pen 102.

[0089] The method begins at step 202. At step 204, controller 116 receives
signals generated by a number of the identification devices 114
positioned at various locations in and/or around free stall pen 102. Each
signal corresponds to a tag affixed to a particular dairy cow 104 located
in a free stall pen 102 at one of a number of times during a time period.
At step 206, controller 116 processes the received signals (e.g., using
RTL logic 122, described above) to determine location information 128
associated with the particular dairy cow 104. The determined location
information 128 may include a coordinate location of the dairy livestock
within the free stall pen 102 at each of the number of times during the
time period (e.g., every fifteen seconds during a one hour time period).
For example, each of the received signals may include information about
the distance from a corresponding identification device 114 to the
particular dairy cow 104. By processing together those signals generated
at or near the same time (e.g., using triangulation based on the distance
information and a known location for each of the corresponding
identification devices 114), controller 116 may determine a coordinate
location (e.g., an (X,Y) location, an (X,Y,Z) location, or any other
suitable coordinate location) of the particular dairy cow 104 within free
stall pen 102 at each of the number of times during the time period.

[0090] At step 208, controller 116 may store the determined location
information 128 associated with the particular dairy cow 104 (e.g., in
memory module 120). At step 210, controller 116 may determine one or more
movement parameters 130 associated with the particular dairy cow 104
(e.g., using estrus detection logic 124, described above) based on at
least a portion of the stored location information 128 associated with
the particular dairy cow 104. For example, the determined movement
parameters 130 may include a stall standing parameter 134, a stall lying
parameter 136, an alley walking parameter 138, and alley lying parameter
140, an alley standing parameter 142, a watering parameter 144, a feeding
parameter 146, a watering count 148, a feeding count 150, a mounting
count 152, a mobility count 154, a distance traveled 156, a turn count
158, and/or a sign change count 160 (each of which are described above
with respect to FIG. 1)

[0091] At step 212, controller 116 may determine whether the particular
dairy cow 104 is likely to be in estrus (e.g., using estrus detection
logic 124, described above) based on the one or more movement parameters
130 associated with the particular dairy cow 104. For example, controller
116 may determine whether the particular dairy cow 104 is likely to be in
estrus by comparing a heat index for the particular dairy cow 104 with a
baseline heat index. If the heat index for particular dairy cow 104 is
greater than the baseline heat index by more than a predefined amount
(e.g., 250%), controller 116 may determine that the particular dairy cow
104 is likely to be in estrus.

[0093] As another example, controller 116 may determine whether the
particular dairy cow 104 is likely to be in estrus by comparing a
distance traveled 156 by the particular dairy cow 104 (e.g., a distance
traveled during a particular time period, as described above) with a
baseline distance traveled. If the distance traveled 156 by the
particular dairy cow 104 is greater than the baseline distance traveled
by more than a predefined amount (e.g., 250%), estrus detection logic 124
may determine that the particular dairy cow 104 is likely to be in estrus
(as an increase in movement of the particular dairy cow 104 may be an
indicator that the particular dairy cow 104 is in estrus).

[0094] As yet another example, controller 116 may determine whether the
particular dairy cow 104 is likely to be in estrus by comparing a turn
index (e.g., turn index=(turn count/hour)×(sign change count/hour))
for a particular dairy cow 104 with a baseline turn index. If the turn
index for particular dairy cow 104 is greater than the baseline turn
index by more than a predefined amount (e.g., 250%), controller 116 may
determine that the particular dairy cow 104 is likely to be in estrus (as
such an increase may be indicative of an increase in pacing by the
particular dairy cow 104, which may be indicative of estrus).

[0095] If controller 116 determines at step 212 that the particular dairy
cow 104 is likely to be in estrus, the method proceeds to step 214.
Otherwise, the method returns to step 204. At step 214, controller 116
may confirm the determination that the particular dairy cow 104 is likely
to be in estrus. For example, controller 116 may confirm the estrus
determination by accessing stored information associated with the
particular dairy cow 104 (e.g., stored in memory module 120) to determine
if the particular dairy cow 104 is near the twenty-first day of her
cycle. As an additional example, controller 116 may initiate the
generation of a signal to be communicated to identification devices 114,
the signal causing identification devices 114 to increase the frequency
with which the tag of the particular dairy cow 104 is read (e.g., from
fifteen seconds to five seconds). As a result, updated location
information 128 may be generated, movement parameters 130 may be
recalculated based on that updated location information 128, and a
subsequent determination regarding whether the particular dairy cow 104
is likely to be in estrus may be made (in a manner substantially similar
to that described above). As yet another example, controller 116 may
access location information for other dairy cows 104 in free stall pen
102 to identify those other dairy cows 104 within a predefined distance
of the particular dairy cow 104 in order to determine (1) whether any
dairy cow 104 located near the particular dairy cow 104 is mounting the
particular dairy cow 104 and/or (2) whether the particular dairy cow 104
is a member of a SAG (each of which is described above with regard to
FIG. 1). At step 216, the method ends.

[0096] Although the steps of method 200 have been described as being
performed in a particular order, the present disclosure contemplates that
the steps of method 200 may be performed in any suitable order, according
to particular needs.

[0097] FIG. 3 illustrates an example method 300 for health monitoring,
according to certain embodiments of the present disclosure. Although
method 300 is described with regard to a particular dairy cow 104, the
present disclosure contemplates a substantially similar method being
performed with regard to each of the plurality of dairy cows 104 in free
stall pen 102.

[0098] The method begins at step 302. At step 304, controller 116 receives
signals generated by a number of the identification devices 114
positioned at various locations in and/or around free stall pen 102. At
step 306, controller 116 processes the received signals (e.g., using RTL
logic 122, described above) to determine location information 128
associated with the particular dairy cow 104. At step 308, controller 116
may store the determined location information 128 associated with the
particular dairy cow 104 (e.g., in memory module 120). Steps 304-308 may
be performed in a substantially similar manner to steps 204-208,
described above with regard to FIG. 2.

[0099] At step 310, controller 116 may determine one or more movement
parameters 130 associated with the particular dairy cow 104 (e.g., using
health monitoring logic 126, described above) based on at least a portion
of the stored location information 128 associated with the particular
dairy cow 104. For example, the determined movement parameters may
include a stall standing parameter 134, a stall lying parameter 136, an
alley walking parameter 138, an alley lying parameter 140, an alley
standing parameter 142, a watering parameter 144, a feeding parameter
146, a watering count 148, and/or feeding count 150 (each of which are
described above with respect to FIG. 1).

[0100] At step 312, controller 116 may determine whether the particular
dairy cow 104 is likely unhealthy (e.g., using health monitoring logic
126, described above) based on the one or more movement parameters 130
associated with the particular dairy cow 104. For example, controller 116
may determine whether the particular dairy cow 104 is likely unhealthy by
comparing a health index for the particular dairy cow 104 with a baseline
health index. If the health index for particular dairy cow 104 is greater
than the baseline health index by more than a predefined amount (e.g.,
250%), controller 116 may determine that the particular dairy cow 116 is
likely unhealthy. In embodiments in which the health index corresponds to
a function of a stall standing parameter 134, a stall lying parameter
136, an alley walking parameter 138, an alley lying parameter 140, an
alley standing parameter 142 a watering parameter 144, a feeding
parameter 146, a watering count 148, and/or a feeding count 150, an
increase in activity in certain portions of free stall pen 102 (e.g., an
increase in the amount of time spent lying in walking alleys 108) may be
an indicator that the particular dairy cow 104 is unhealthy.

[0101] If controller 116 determines at step 312 that the particular dairy
cow 104 is likely unhealthy, the method proceeds to step 314. Otherwise,
the method ends at step 316. At step 314, controller 116 may confirm the
determination that the particular dairy cow 104 is likely unhealthy. For
example, controller 116 may initiate the generation of a signal to be
communicated to identification devices 114, the signal causing
identification devices 114 to increase the frequency with which the tag
of the particular dairy cow 104 is read (e.g., from fifteen seconds to
five seconds). As a result, updated location information 128 may be
generated, movement parameters 130 may be recalculated based on that
updated location information 128, and a subsequent determination
regarding whether the particular dairy cow 104 is likely unhealthy may be
made (in a manner substantially similar to that described above). If the
subsequent determination also indicates that the particular dairy cow 104
is likely unhealthy, the initial determination may be confirmed. At step
316, the method ends.

[0102] Although the steps of method 300 have been described as being
performed in a particular order, the present disclosure contemplates that
the steps of method 300 may be performed in any suitable order, according
to particular needs.

[0103] Although the present invention has been described with several
embodiments, diverse changes, substitutions, variations, alterations, and
modifications may be suggested to one skilled in the art, and it is
intended that the invention encompass all such changes, substitutions,
variations, alterations, and modifications as fall within the spirit and
scope of the appended claims.